Nov 2026· SAE technical papers on CD-ROM/SAE technical paper series· 12 references
Software-Defined Networks and 5G
Abstract
Low-altitude Communication Network (LCN) refers to network systems that employ drones and other low-altitude aerial platforms as carriers. Leveraging advanced communication technologies and data processing methodologies, these networks enable high-efficiency data transmission in low-altitude airspace, thus emerging as a pivotal driver for the advancement of the low-altitude economy. With the continuous advancement of Unmanned Aerial Vehicle (UAV), artificial intelligence, and communication technologies, LCN have been increasingly integrated into smart city construction, Internet of Things expansion, emergency management, and other fields. As a core component of these sectors, LCN have effectively driven the robust development of the low-altitude economy. Within the context of LCN, the efficient deployment of Service Function Chain (SFC) emerges as a critical factor in optimizing network service capabilities and enhancing resource utilization efficiency. In the dynamic and complex operating environment of LCN, reasonable and efficient SFC deployment can effectively coordinate the allocation of communication, computing, and storage resources, laying a solid foundation for the stable and high-quality operation of various network services. However, existing deployment algorithms either fail to fully consider the dynamic changes in the LCN or lack sufficient exploratory strategies, making them difficult to adapt to the diverse business scenarios within the LCN. To address the issue, our study proposes a dynamic SFC deployment method based on the Asynchronous Advantage Actor-Critic (A3C) and Graph Attention Network (GAT) algorithms. The experimental findings indicate that our proposed algorithm achieves a notable reduction in orchestration expenses, while simultaneously enhancing resource utilization, thus exhibiting excellent performance and robust adaptability in dynamic LCN environments.
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9